Rose, a Potential Nutraceutical: An Assessment of the Total Phenolic Content and Antioxidant Activity
Bibliographic record
Abstract
Rosa hybrida L. was reported to contain high total phenolic content and antioxidant activity. The scarce information on antioxidant properties of Malaysian cultivated R. hybrid L. had lead to the present study, which aimed to determine the effect of different solvent extraction on the total phenolic content and antioxidant activity of roses of different colours. All the 23 R. hybrida L. cultivars’ petals extracted with 70% ethanol had significantly higher 2,2-diphenyl-1-picryl-hydrazyl (DPPH) radical scavenging activity compared to the water extraction. The five cultivars (03, 203, 205, 402 and M203) that comprise the highest DPPH scavenging activity were subjected to various antioxidant assays. Cultivar M203 showed highest total phenolic content (TPC) at all concentration. Cultivar M203 and 402 gave higher DPPH radical scavenging ability (EC50=107.08 µg/ml) and 2,2-azino-bis(3-ethylbenzo-thiazoline-6-sulfonic acid) (ABTS) radical cation scavenging ability (EC50=258.13 µg/ml). In ferric reducing antioxidant power assay, cultivar M203 has the highest trolox equivalent value at 200, 300 and 500 µg/ml concentrations while in b-carotene bleaching assay, cultivars 03, 205, and M203 (at the concentration of 500 µg/ml) showed higher antioxidant activity than synthetic antioxidant (BHA). Strong positive correlations were found between TPC and antioxidant activities, hence, suggesting that the high antioxidant activity of selected R. hybrida L. petals might be mainly contributed by the phenolic compounds. In general, cultivar M203 showed the best antioxidant activity with nutraceutical potential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".